Q-omics provides the consensus-scored FKBP2 profile across patient tissues and cancer cell-line models. FKBP2 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, FKBP2 is differentially expressed in 11, with the highest sampling consensus in LIHC. Additionally, FKBP2 RNA expression shows 18,142 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight UVM, LIHC, and THYM as cancer lineages where FKBP2 shows reproducible signals across survival, tumor–normal expression, and patient cross-omics analyses.
Every result is evaluated using two consensus scores. Sampling consensus measures how consistently a finding is reproduced within a cancer lineage across different conditions. Lineage consensus measures how broadly the result is shared across cancer types, distinguishing pan-cancer signals from lineage-specific patterns.
Premium analyses for FKBP2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes FKBP2 survival associations across molecular data types. FKBP2 RNA expression shows survival associations in the most cancer types (23). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible FKBP2 RNA expression–survival associations across cancer types. High FKBP2 expression shows unfavorable associations in UVM, KICH, ACC, LGG and COAD, but favorable associations in OV. The UVM Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p < 0.001). Together, the overview and detailed table identify UVM as the clearest survival context for FKBP2 RNA expression.
This table summarizes FKBP2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11. The strongest signals are observed in LIHC for RNA.
This table ranks reproducible tumor–normal expression differences for FKBP2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. FKBP2 shows lower tumor expression in THCA and COAD and higher tumor expression in LIHC, HNSC, LUAD and STAD. The LIHC box plot shows higher FKBP2 RNA expression in tumor versus normal tissue (log2 FC = +0.766, t-test p < 0.001).
This table shows molecular features associated with FKBP2 in patient tissues and cancer cell lines. In patient samples, FKBP2 shows the broadest associations at the RNA and protein expression levels, with THYM recurring as the lineage with the largest associated feature set. In cancer cell lines, FKBP2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SOFT_TISSUE, while CRISPR and shRNA rows add functional-dependency signals in URINARY_TRACT and LUNG_SCLC.
